Sepsis

Weekly ILI patient ratio change prediction using news articles with support vector machine.

BACKGROUND: Influenza continues to pose a serious threat to human health worldwide. For this reason,...

A machine learning approach for predicting urine output after fluid administration.

BACKGROUND AND OBJECTIVE: To develop a machine learning model to predict urine output (UO) in sepsis...

Multiple tracking and machine learning reveal dopamine modulation for area-restricted foraging behaviors via velocity change in Caenorhabditis elegans.

Food exploration is an essential survival behavior in organisms. To find food efficiently, many orga...

Streptococcus Gallolyticus endocarditis in patient with liver cirrhosis: a case report.

Streptococcus gallolyticus (S. gallolyticus) bacteremia is commonly associated with endocarditis and...

Construction and optimization of a 'NG Morbidostat' - An automated continuous-culture device for studying the pathways towards antibiotic resistance in .

To obtain a detailed picture of the dynamics of antibiotic resistance development in , we built a mo...

Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs.

OBJECTIVE: Sepsis remains a costly and prevalent syndrome in hospitals; however, machine learning sy...

Refining humane endpoints in mouse models of disease by systematic review and machine learning-based endpoint definition.

Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's disco...

Feasible Classified Models for Parkinson Disease from Tc-TRODAT-1 SPECT Imaging.

The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomog...

Fast and reliable determination of Escherichia coli susceptibility to antibiotics: Infrared microscopy in tandem with machine learning algorithms.

Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, th...

Booster immunity - diagnosis of chronic hepatitis B viral infection.

INTRODUCTION: Diagnosis of chronic hepatitis B virus (HBV) infection particularly its occult form re...

In vitro anti-Trichomonas vaginalis activity of Haplophyllum myrtifolium.

INTRODUCTION: In the classic treatment of Trichomonas vaginalis infection, although metronidazole ha...

Heterologous Machine Learning for the Identification of Antimicrobial Activity in Human-Targeted Drugs.

The emergence of microbes resistant to common antibiotics represent a current treat to human health....

Dissecting the Catecholamines: How New Approaches Will Facilitate the Distinction between Noradrenergic and Dopaminergic Systems.

To overcome the limitations of fast scan cyclic voltammetry (FSCV) to discriminate between catechola...

Application of convolutional neural networks for evaluating Helicobacter pylori infection status on the basis of endoscopic images.

BACKGROUND AND AIM: We recently reported the role of artificial intelligence in the diagnosis of Hel...

Interpretable genotype-to-phenotype classifiers with performance guarantees.

Understanding the relationship between the genome of a cell and its phenotype is a central problem i...

Emotional arousal amplifies competitions across goal-relevant representation: A neurocomputational framework.

Emotional arousal often facilitates memory for some aspects of an event while impairing memory for o...

Predictive markers for Parkinson's disease using deep neural nets on neuromelanin sensitive MRI.

Neuromelanin sensitive magnetic resonance imaging (NMS-MRI) has been crucial in identifying abnormal...

Novel Machine Learning Identifies Brain Patterns Distinguishing Diagnostic Membership of Human Immunodeficiency Virus, Alcoholism, and Their Comorbidity of Individuals.

The incidence of alcohol use disorder (AUD) in human immunodeficiency virus (HIV) infection is twice...

Multiple Machine Learning Comparisons of HIV Cell-based and Reverse Transcriptase Data Sets.

The human immunodeficiency virus (HIV) causes over a million deaths every year and has a huge econom...

A novel machine-learning-based infection screening system via 2013-2017 seasonal influenza patients' vital signs as training datasets.

Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data.

BACKGROUND: Rapid antibiotic administration is known to improve sepsis outcomes, however early diagn...